Update app.py

app.py

@@ -100,9 +100,9 @@ def image_to_3d(
     slat_guidance_strength: float,
     slat_sampling_steps: int,
     req: gr.Request,
-) -> Tuple[dict, str]:
+) -> Tuple[dict, str, str]:
     """
-    Convert an image to a 3D model.
+    Convert an image to a 3D model and save full-quality GLB.
     """
     user_dir = os.path.join(TMP_DIR, str(req.session_hash))
     outputs = pipeline.run(
@@ -119,39 +119,30 @@ def image_to_3d(
             "cfg_strength": slat_guidance_strength,
         },
     )
-    video = render_utils.render_video(outputs['gaussian'][0], num_frames=20)['color']
-    video_geo = render_utils.render_video(outputs['mesh'][0], num_frames=20)['normal']
+
+    # Generate video preview
+    video = render_utils.render_video(outputs['gaussian'][0], num_frames=120)['color']
+    video_geo = render_utils.render_video(outputs['mesh'][0], num_frames=120)['normal']
     video = [np.concatenate([video[i], video_geo[i]], axis=1) for i in range(len(video))]
     trial_id = str(uuid.uuid4())
     video_path = os.path.join(user_dir, f"{trial_id}.mp4")
     imageio.mimsave(video_path, video, fps=15)
-    
-    state = pack_state(outputs['gaussian'][0], outputs['mesh'][0], trial_id)
-    return state, video_path
 
-@spaces.GPU
-def export_full_quality_glb(
-    state: dict,
-    req: gr.Request,
-) -> Tuple[str, str]:
-    """
-    Export a full-quality GLB file from the 3D model state.
-    """
-    user_dir = os.path.join(TMP_DIR, str(req.session_hash))
-    gs, mesh, trial_id = unpack_state(state)
-    
+    # Create full quality GLB while we have the data in memory
+    full_glb_path = os.path.join(user_dir, f"{trial_id}_full.glb")
     glb = postprocessing_utils.to_glb(
-        gs,
-        mesh,
+        outputs['gaussian'][0],
+        outputs['mesh'][0],
         simplify=0.0,  # No simplification
         fill_holes=True,
         fill_holes_max_size=0.04,
         texture_size=2048,  # Maximum texture resolution
         verbose=False
     )
-    glb_path = os.path.join(user_dir, f"{trial_id}_full.glb")
-    glb.export(glb_path)
-    return glb_path, glb_path
+    glb.export(full_glb_path)
+    
+    state = pack_state(outputs['gaussian'][0], outputs['mesh'][0], trial_id)
+    return state, video_path, full_glb_path
 
 @spaces.GPU
 def extract_glb(
@@ -161,7 +152,7 @@ def extract_glb(
     req: gr.Request,
 ) -> Tuple[str, str]:
     """
-    Extract a GLB file from the 3D model.
+    Extract a reduced-quality GLB file from the 3D model.
     """
     user_dir = os.path.join(TMP_DIR, str(req.session_hash))
     gs, mesh, trial_id = unpack_state(state)
@@ -174,9 +165,8 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
     gr.Markdown("""
     ## Image to 3D Asset with [TRELLIS](https://trellis3d.github.io/)
     * Upload an image and click "Generate" to create a 3D asset. If the image has alpha channel, it be used as the mask. Otherwise, we use `rembg` to remove the background.
-    * After generation:
-        * Extract full-quality GLB for maximum detail
-        * Or use the GLB Extraction Settings for a reduced size version
+    * The full-quality GLB will be available immediately after generation.
+    * You can also create a reduced size version using the GLB Extraction Settings.
     """)
     
     with gr.Row():
@@ -196,7 +186,6 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
                     slat_sampling_steps = gr.Slider(1, 500, label="Sampling Steps", value=12, step=1)
 
             generate_btn = gr.Button("Generate")
-            extract_full_btn = gr.Button("Extract Full GLB", interactive=False)
             
             with gr.Accordion(label="GLB Extraction Settings", open=False):
                 mesh_simplify = gr.Slider(0.0, 0.98, label="Simplify", value=0.95, step=0.01)
@@ -244,19 +233,10 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
     ).then(
         image_to_3d,
         inputs=[image_prompt, seed, ss_guidance_strength, ss_sampling_steps, slat_guidance_strength, slat_sampling_steps],
-        outputs=[output_buf, video_output],
+        outputs=[output_buf, video_output, download_full],
     ).then(
-        lambda: [gr.Button(interactive=True), gr.Button(interactive=True)],
-        outputs=[extract_full_btn, extract_glb_btn],
-    )
-
-    extract_full_btn.click(
-        export_full_quality_glb,
-        inputs=[output_buf],
-        outputs=[model_output, download_full],
-    ).then(
-        lambda: gr.Button(interactive=True),
-        outputs=[download_full],
+        lambda: [gr.Button(interactive=True), gr.Button(interactive=True), gr.Button(interactive=False)],
+        outputs=[download_full, extract_glb_btn, download_reduced],
     )
 
     extract_glb_btn.click(